Abstract P263: Computer-Assisted Decision Support in the Treatment of Acute Coronary Syndromes and Impact on Cardiovascular Outcomes

Abstract

Background: Evidence from clinical trials and consensus guidelines suggest that in-hospital initiation of key therapeutics can reduce mortality and morbidity in patients admitted with acute coronary syndrome (ACS). As a result, the AHA and ACC have co-developed guideline-based “performance measures” for ACS patients, such that when every measure has been performed, the patient is considered to have achieved optimal or “perfect” care (PC). Computer-assisted decision support (CADS) is a tool that can improve quality of care and is well suited for complex algorithms governing treatment decisions. We sought to determine if CADS tailored to ACS would enhance the likelihood of achieving PC, and whether achievement of PC would translate into reduced mortality. Methods: 452 consecutive patients (mean age 68±13 years) admitted with ACS in 2009 were evaluated (unstable angina 29%, NSTEMI 61%, STEMI 10%). Physicians had the option of using either pre-printed ACS orders (standard orders) versus CADS generated orders. The CADS system utilized patient clinical data including risk scoring, to suggest specific therapeutics and drug dosing based on consensus guidelines. Endpoints were attainment of PC and 30-day mortality. Results: The 77 patients admitted using CADS generated orders were statistically similar (age, gender, ACS diagnosis, TIMI risk) to the 375 patients admitted with the standard order set. Attainment of PC was almost twice as likely when using CADS versus standard orders (84% vs. 44%, p<0.05). PC patients trended towards higher TIMI risk scores (3.2 ±1.7 vs 2.9 ±1.6, p = 0.09) but had half the 30-day mortality (2% vs 4%, p=0.05) compared to patients not achieving PC. Conclusions: Use of CADS in the setting of ACS is feasible and doubles the likelihood of attaining PC. Although patients achieving PC had higher baseline risk, their mortality was reduced by 50% compared to those not achieving PC. These data support the use of CADS in the setting of ACS to improve quality of care and subsequent outcomes.